Data Engineer

About us
Omniscient delivers real-time intelligence that helps organisations and leaders make better decisions, faster. Our platform brings together public and internal data to help corporates, investors and public institutions detect risks, understand shifts in their environment and act with greater confidence. Combining intuitive dashboards with AI-powered analysis, Omniscient turns complex, fast-moving signals into clear, actionable intelligence, from reputation monitoring and geopolitical developments to competitive positioning and narrative change. We help decision-makers track what matters across their ecosystem, benchmark against peers, and stay ahead of emerging threats and opportunities. The role We are hiring a data engineer: a pragmatic builder who owns the data platform end to end, from raw source to the signal a client acts on. Ingestion, pipelines, storage, APIs, retrieval, data quality, cost, production. The role is broad by design. Most of your time will go to data, but not all of it. We are a small team: when the fire is elsewhere, you go there. If you see anything outside data engineering as someone else’s problem, this is not the role for you. We need someone who builds reliably, thinks in systems, uses coding agents effectively, and helps the team ship faster without compromising quality. What you will do
• Product mindset. Understand clients, understand features, generate ideas. Know what an analyst does with the data you deliver. Own part of the PO or PM duties on the data side.
• Architecture. Think about several approaches, ponder trade-offs, socialise decisions, document them. Choose patterns that fit the situation. Plan for scaling, cost and resiliency. Make tomorrow work while delivering today.
• Ingestion. Collect text, image and video signals at scale: news, social media, web, reviews, licensed feeds, client internal data. Build and maintain connectors. Handle rate limits, deduplication, backfills, schema drift and sources that break without warning.
• Pipelines. Databricks and Spark. Batch and streaming for near real-time processing. Orchestration, idempotency, replay. Pipelines that recover on their own rather than waking someone up.
• Data stores. Azure SQL, Azure AI Search, storage accounts, Redis, vector store. Model the data so it stays cheap to query and easy to reason about as volume grows.
• APIs. Build and maintain the APIs that expose the DataHub to the rest of the platform: C#, SQL, containers, Redis cache. Fast, reliable, documented.
• AI and retrieval. Embeddings, chunking, indexing, retrieval quality. Consume and shape the scoring endpoints that classify, translate, enrich and qualify entries. Feed the agents layer with context it can actually use.
• Data quality. Cleaning, coverage, freshness, deduplication, multilingual handling, entity resolution. Test the data, not only the code. A silent gap in coverage is a bug.
• Beyond data. Work across the platform wherever you are needed: tenant-specific code, side projects, GTM tooling. Ownership does not stop at the edge of the DataHub.
• Infra. Terraform cloud infra (primarily Azure, some AWS). Secure it. Keep costs in check: ingestion and scanning spend is a first-class design constraint, not an afterthought.
• QA. Write automated tests for everything you do (unit, integration and post-deployment). Occasionally do some exploratory checks on real data.
• DevOps. Keep CD pipelines green. Adapt them.
• Production. You build it, you run it. You take your turn on call. Monitoring is not an option.
• Productivity. Use coding agents wisely. Write skills and routines. Automate what can be automated. Constantly strive to increase the productivity of the team. What we look for
• Python and SQL. The daily languages, and you are fluent in both.
• C# as well. Our back end runs on C# and Python, and you are comfortable enough in C# to ship in it. Experience in another statically typed language is a good starting point.
• End-to-end ownership. You have owned data systems end to end and shipped them into production. We care more about slope than about years on a CV.
• A builder at heart. You have a genuine passion for shipping slick products. Here, that means crafting a new form of executive intelligence.
• Agentic development. We are an AI-powered organisation, laser-focused and built around efficiency and agentic workflows. You already build with coding agents (Claude Code, Codex, Cursor or similar) and they are central to how you work. You keep learning, look for better ways, automate your own work and share with your peers. We want people with the same drive to build fast and efficiently.
• Fundamentals over framework years. With agents, we need fewer specialists in one tool and more people with sharp concepts and the appetite to learn. We do not need eight years in each of our frameworks.
• Fluent professional English. You work with colleagues and clients in English without friction. French is a plus, not a requirement.
• Paris. Based in Paris or ready to move, and in the office at least three days a week. We know it’s a lot, and we don’t expect you to know everything: equivalent technologies and experiences count too. But learn, be afraid of nothing, collaborate, and grow. And Claude is here to help. Desired character traits: autonomy, team player, flexible, fast learner, committed. How we work
• Make it happen. We are a startup. When something needs doing, we do it and learn what we need on the way. Everyone has a spike, everyone works across the stack, and “not my speciality” is not something we say.
• You build it, you run it. There is no separate ops team. Each of us owns observability, alerts and incidents for what we ship, and we share an on-call rotation across the working week. Our clients rely on Omniscient when they face a crisis: being down at that moment is not an option.
• No single point of failure. Every critical system is known by at least two people, with the access to match.
• Agents everywhere. We build with coding agents every day. We expect you to multiply yourself with them: write skills and routines, run loops, industrialise what works, and share it with the team. The essentials
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Location:
Paris, in the office at least three days a week
• Contract: permanent (CDI), full-time
• Languages: fluent English required, French a plus
• Start: as soon as possible